For all of numpy's faults I find it odd that you choose its indexing and broadcasting API as the thing that's confusing and worse than equivalents in Mathematica and R. I can't speak to Julia or Matlab, but I find working with arrays in the other two is like pulling teeth.

I'm curious what the outcome would be if we ran a poll asking what people find easier. I find numpy's API more intuitive, but I could be a minority.

I will say that the differences between python and R syntax are almost trivial; I've taught classes with python and R example scripts that are almost _exactly_ the same, and run in both languages

I like R, but there is nothing elegant or consistent about its standard library. I don’t think you’re making a good-faith argument.

Don’t just randomly accuse people of making bad faith arguments. I’ve use R a lot and while it has its issues, it has a much better interface than numpy.

Well they're different, right?

R provides an interface to dataframes and matrices, whereas numpy is just for matrices (and their generalisations, arrrays). I think the appropriate comparison is between base R and Numpy + pandas. (FWIW, I agree with your major point, but then I learned R first so that may be biasing me).

It’s hardly random. R functions could be noun-adjective or adjective-noun or underscored or camelCase or dotted ... and that’s just naming conventions. If someone, like you, says that Numpy sucks, but R is the real masterpiece, then that’s totally insincere. The good thing about R is that it’s free, the C FFI is OK and R-studio is decent. It’s API is a patchwork. It’s cool to say Java sucks or Python sucks on the orange site because they’re popular and if you say something popular sucks, well you must be a pretty cool guy who is smarter than all those rubes out there. The arguments are almost always total nonsense, though.